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Record W4409376445 · doi:10.1080/19434472.2025.2486796

Exploring the evolution of posting behavior and language use in a racially and ethnically motivated extremist forum

2025· article· en· W4409376445 on OpenAlex
Sydney Litterer, Ryan Scrivens, Thomas Wojciechowski, Richard G. Frank

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBehavioral Sciences of Terrorism and Political Aggression · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEthnically diverseViolent extremismTerrorismCriminologyEthnic groupPsychologyPolitical scienceSocial psychologySociologyLaw

Abstract

fetched live from OpenAlex

Researchers, practitioners, and policymakers are increasingly interested in examining online posting behaviors in virtual communities known to facilitate violent racially and ethnically motivated extremism. However, little is empirically known about how such behaviors develop over time, and even less is known about how the content of posts is related to other posting behaviors. This study used group-based multi-trajectory modeling to explore how users’ online posting behaviors (i.e., posting frequency and use of offensive language) evolved as they engaged with other users on Stormfront, the largest and most well-known white supremacist forum, relative to typical user behaviors. Overall, several noteworthy posting behaviors were identified in the data. We conclude with a discussion of the implications of the analysis, its limitations, and avenues for future research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.384
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it